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The primary objective of the paper is to examine the asymmetric Cointegration and asymmetric causality between financial development and poverty alleviation on annual data in Indian context over the period from 1980 to 2019.

First nonlinearity test by Brooks et al. (1999) is applied to ascertain the nonlinear behavior of the variables used. Once the nonlinear behavior of variables is confirmed, asymmetric and nonlinear unit root tests by Kapetanios and Shin (2008) are applied to check for the order of integration of selected variables. Next, nonlinear autoregressive distributed lag model (NARDL) is employed to analyze the asymmetric Cointegration. Finally, Hatemi-j- asymmetric causality tests is applied to work out the direction of asymmetric causality.

The empirical findings document the existence of asymmetries in the short-run as well as long-run between poverty and financial development. The asymmetry reveals that negative financial development shocks leave a more profound impact on poverty alleviation than their positive equivalents. The findings of Wald's test also confirm the presence of asymmetric Cointegration. The asymmetric cumulative dynamic multipliers used to examine the behavior of asymmetries and adjustments with respect to time lend credence to the results calculated using NARDL estimator. This result exhibits the robustness of the model. Furthermore, the result emanating from recently introduced asymmetric causality test reveals a unidirectional asymmetric causality between negative shocks in financial development and poverty. The findings of the present study necessitate the need for investigating asymmetric and nonlinear effects in finance–poverty nexus, which existent literature has completely neglected, in order to have relevant policy conclusions.

The study used “Per capita consumption expenditure” as a measure for poverty due to lack of continuous time series data on headcount ratio. In future, researchers can extend this study by incorporating headcount ratio as a measure of poverty in their respective works. There is further scope of research on this issue by finding out the impact of formal and informal sources of credit on poverty separately. A panel data study for developing countries over a period of time could further confirm/negate the findings of the present study.

To the best of the authors’ knowledge none of the studies in Indian context has scrutinized asymmetric and nonlinear impact of financial development on poverty. To dredge up asymmetric structures at work, the authors have used the highly celebrated NARDL estimator. To enrich the existent body of knowledge along the lines of asymmetric (nonlinear) linkages, the authors have also used recently introduced asymmetric causality test by Hatemi-j-(2012) to find out the direction asymmetric causality.

The purpose of this study is to examine how US farm sector performed in 2020, the first year of the pandemic. There were significant supply and demand shocks due to the pandemic. Furthermore, there was significant fluctuation in commodity prices and record high government payments in 2020. This study aims to examine the performance and position of US farm sector (financially) to system (and global economy) wide shocks.

The authors examine 2020 values for farm sector financial ratios before and after the onset of the Coronavirus (COVID-19) pandemic using the data from the United States Department of Agriculture to understand the financial position and performance of the US farm sector.

The authors find solvency ratios (which are indicators of the sector's ability to repay financial liabilities via the sale of assets) worsened in 2020 relative to pre-pandemic expectations. Efficiency ratios (which evaluate the conversion of assets into production and revenue) and liquidity ratios (which are indicators of the availability of cash to cover debt payments) showed mixed outcomes for the realized results in 2020 relative to the pre-pandemic forecasts. Four profitability ratios were stronger in 2020 relative to pre-pandemic expectations. All solvency, liquidity and profitability ratios plus 2 out of 5 efficiency ratios for 2020 were weaker than their respective average ratios obtained from 2000 to 2019 data.

This research is one of the first papers to use financial ratios to examine how the US farm sector performed in 2020 compared to expectations prior to the pandemic.

Sequel to the results of the preceding chapter that depicted positive associations of credit with the indicators of growth and development, the present chapter aims at investigating the interrelationships of credit with GDP and HDI separately in a bivariate framework for the selected countries for the period 1990–2019. For this purpose, this chapter first develops a theoretical model in line with the Barro (1991) model where bank credit is introduced as a good institutional component of endogenous growth. Then, it goes for a time series exercise to establish the long-run relations and short-run dynamics for the pairs of variables, credit-GDP and credit-HDI, to justify the linkages between the financial sector and the real sector. The study arrives at mixed results across the countries. In many cases, credit has been identified to be strongly related to income and development indicators in the long run through cointegrated stable relationships. Furthermore, credit makes a causal influence on GDP and HDI in some developed countries whereas GDP becomes a causal factor to credit in some developing countries. It is thus recommended for further aggravation of the two sectors’ linkages under the patronisations of the governments and the monetary authorities of the countries to have high growth of income and development so that a part of the sustainable development goal can be achieved through the financial sector.

This study examines the roles of cross-sectional dependence, asymmetric structure and country-to-country policy variations in the inflation-poverty reduction causal nexus in selected sub-Saharan African (SSA) countries from 1981 to 2019.

To account for cross-sectional dependence, heterogeneity and policy variations across countries in the inflation-poverty reduction causal nexus, this study uses robust Hatemi-J data decomposition procedures and a battery of second-generation techniques. These techniques include cross-sectional dependency tests, panel unit root tests, slope homogeneity tests and the Dumitrescu-Hurlin panel Granger non-causality approach.

Unlike existing studies, the panel and country-specific findings exhibit several dimensions of asymmetric causality in the inflation-poverty nexus. Positive inflationary shocks Granger-causes poverty reduction through investment and employment opportunities that benefit the impoverished in SSA. These findings align with country-specific analyses of Botswana, Cameroon, Gabon, Mauritania, South Africa and Togo. Also, a decline in poverty causes inflation to increase in the Congo Republic, Madagascar, Nigeria, Senegal and Togo. All panel and country-specific analyses reveal at least one dimension of asymmetric causality or another.

All stakeholders and policymakers must pay adequate attention to issues of asymmetric structures, nonlinearities and country-to-country policy variations to address country-specific issues and the socioeconomic problems in the probable causal nexus between the high incidence of extreme poverty and double-digit inflation rates in most SSA countries.

Studies on the inflation-poverty nexus are not uncommon in economic literature. Most existing studies focus on inflation’s effect on poverty. Existing studies that examine the inflation-poverty causal relationship covertly assume no asymmetric structure and nonlinearity. Also, the issues of cross-sectional dependence and heterogeneity are unexplored in the causal link in existing studies. All panel studies covertly impose homogeneous policies on countries in the causality. This study relaxes this supposition by allowing policies to vary across countries in the panel framework. Thus, this study makes three-dimensional contributions to increasing understanding of the inflation-poverty nexus.

The financial system plays an essential role in facilitating the intermediation process for economic growth. Policymakers stress on achieving a well-developed and regulated financial system to achieve economic development and resiliency. Using data from the State of Qatar, this paper aims to examine the impact of financial development indicator on economic growth; the impact of financial development indicator on hydrocarbon and nonhydrocarbon sector; the impact of Islamic banking on hydrocarbon and nonhydrocarbon economic growth.

The research uses quarterly data from 2007 to 2019 and adopts autoregressive distributed lag cointegration techniques to test the long- and short-run dynamic relationship between various measures of financial development and economic growth.

The results present evidence of long-term cointegration between overall financial development indicator and economic growth. Furthermore, the authors document the existence of long-term relationship between financial development and nonhydrocarbon sector. However, there is a lack of evidence on the long-run relationship between financial development and the hydrocarbon sector. Notwithstanding, Islamic banking contributes to overall economic development, as well as to the nonhydrocarbon sector.

This paper offers policymakers with insights to evaluate measures to diversify the economy. It also assists decision-makers in promoting Islamic finance, particularly to the banking sector as a vital contributor to economic growth.

To the best of the author’s knowledge, this paper is the first to evaluate financial development and economic growth for the case of Qatar in light of recent developments in Islamic finance.

The literature on sustainable development reveals that the financial sector and the real sector should maintain a coherent association in the long run. Thus, like that in a country-level significance, the relevance of the investigations of the interrelationships between the financial sector’s development and the growth and development of the states within a country is also required to be done. This chapter tries to examine the interrelationships between two sets of variables, bank credit and state output, and bank credit and human development, for the pre-reform and post-reform periods. Using the appropriate time series econometric analysis, the study finds no long-run relationships between credit and NSDP during the pre-reform period but it has observed a number of states where such stable relations hold during the post-reform period. Again, there are mixed results between the two in the Granger causality analysis during both the periods. There are the states like AP, Bihar, Karnataka, Kerala and WB where developments in the financial sector influence the growth of the real sector, while the reverse causality, that is, from the real sector to the financial sectors works in case of Assam, Haryana, MP and Maharashtra. Bidirectional causality between the two is observed in the states like TN, WB, etc. Further, the study finds very small number of states where credit and human development are interlinked in the long run. However, in the short run, the financial sector makes influences to the human development in case of the states like Bihar, Odisha and TN.

The principal aim of this study is to examine the relationship between financial development and income inequality in India using the financial Kuznets curve (FKC) hypothesis.

This study uses the autoregressive distributed lag (ARDL) model and the Toda–-Yamamoto causality test to investigate the long-run and short-run relationship and causality between financial development and income inequality. In addition, this study employs a principal component analysis (PCA) to construct a comprehensive financial development index.

The study found a long-run relationship between financial development and income inequality in India for the period under consideration. Trade is found to improve the income distribution, while inflation worsens income distribution. Moreover, the empirical results revealed a feedback causality between financial development and income inequality. The study results confirm an inverted U-shaped relationship between financial sector development indicators and income inequality, thus validating the FKC hypothesis for the Indian economy.

The study draws attention of the government and policymakers, urging them to focus on building a strong financial sector by improving its efficiency. This, in turn, will lead to enhanced financial stability and a reduction in income inequality. They should prioritise the development of high-quality and sustainable financial products and services to ensure the robust growth of the financial sector.

To the best of our knowledge, this study is the latest of its kind to empirically test the financial development on income inequality and the FKC hypothesis simultaneously for the Indian economy using financial proxy variables from financial institutions (FIs) and financial markets (FMs) for the measurement of financial depth.

The financial system of an economy, especially banking, facilitates efficient allocation of resources from savers to borrowers for productive investments, and thus promotes economic growth. State-wise bank credit in India shows a growing divergence, despite the aim of central planning to reach a degree of convergence in macroeconomic performance over time. This chapter analyzes how diverging bank credit affects macroeconomic performances of the Indian states, through an alternative approach of composite indicators-based rankings of states adopting the methodology of TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) that is used in operations research or more specifically MCDM (multiple criteria decision-making). A composite indicator of the states’ annual macroeconomic performances has been constructed taking indicators of output growth, per capita state domestic product, inflation, and fiscal indicators for years 2006–2018. States are ranked by both macroeconomic performance and bank credit to states, and the correlation between the two indicators, known in the literature to be interlinked,is studied here to understand how the availability of credit or lack of it has influenced State level macroeconomic development in India. The results thus show that wealthier and better performing states continue to attract the larger chunk of bank credit, while weaker states have not been able to catch up. An important policy implication would be to place even more emphasis on higher levels of credit growth for weaker states, particularly infrastructure credit, to achieve a degree of income convergence throughout the Indian economy.

The objective of this study is to examine the moderating effect of microfinance on the digital divide in developing countries.

On the methodology, the econometric method employed to estimate the equation is based on the two-stage least squares (2SLS).

This study confirms that microfinance can play an important role in mitigating the adverse effect of digitalization on poverty.

Thus, governments should prioritize and encourage the integration of digital technologies with robust microfinance systems to effectively combat poverty, given the importance of microfinance.

Given the importance of digital technology to businesses and economic development, we need to search for a better solution that allows digital technology to be further developed but at the same time, is not harmful to the poor. The issue of the poor, either financially or technically can be partially resolved if the poor is given the necessary and sufficient assistance. Therefore, this paper examines whether microfinance can be part of solutions to the digital divide in developing countries.